NVIDIA TITAN V -VOLTA 12GB HBM2 VIDEO CARD OEM

NVIDIA TITAN V

• 640 TENSOR CORES An Exponential Leap in Performance Every industry needs AI, and with this massive leap forward in speed, AI can now be applied to every industry. Equipped with 640 Tensor Cores, Volta delivers over 100 Teraflops per second (TFLOPS) of deep learning performance, over a 5X increase compared to prior generation NVIDIA Pascal architecture.
• NEW GPU ARCHITECTURE Engineered for the Modern Computer Humanity’s greatest challenges will require the most powerful computing engine for both computational and data science. With over 21 billion transistors, Volta is the most powerful GPU architecture the world has ever seen. It pairs NVIDIA CUDA and Tensor Cores to deliver the performance of an AI supercomputer in a GPU.
• NEXT GENERATION NVLINK Scalability for Rapid Time-to-Solution Volta uses next generation revolutionary NVIDIA NVLink high-speed interconnect technology. This delivers 2X the throughput, compared to the previous generation of NVLink. This enables more advanced model and data parallel approaches for strong scaling to achieve the absolute highest application performance.
• VOLTA-OPTIMIZED SOFTWARE GPU-Accelerated Frameworks and Applications Data scientists are often forced to make trade-offs between model accuracy and longer run-times. With Volta-optimized CUDA and NVIDIA Deep Learning SDK libraries like cuDNN, NCCL, and TensorRT, the industry’s top frameworks and applications can easily tap into the power of Volta. This propels data scientists and researchers towards discoveries faster than before.
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  At its default clocks, the NVIDIA TITAN V offers a peak texture fillrate of 384 GigaTexels/s,  The 12GB of HBM2 memory on-board the GV100 is linked to the GPU via a 3072-bit interface and offers up 652.8 GB/s of peak bandwidth, which is about 100GB/s more than a TITAN Xp. Other features of the GV100 include 5,120 single-precision CUDA cores, 2,560 double-precision FP64 cores, and 640 Tensor cores, which can offer massive performance improvements in Deep Learning workloads, to the tune of up to 110TFLOPs. The cores are arranged in 6 GPCs, with 80 SMs. There are also 320 texture units on board, and 96 ROPs, which is right in-line with the GP102.